We have investigated the accuracy of the templating of digital radiographs in planning total hip replacement using two common object-based
Digital radiography is becoming widespread. Accurate pre-operative templating of digital images of the hip traditionally involves positioning a
To develop and validate patient-centred algorithms that estimate individual risk of death over the first year after elective joint arthroplasty surgery for osteoarthritis. A total of 763,213 hip and knee joint arthroplasty episodes recorded in the National Joint Registry for England and Wales (NJR) and 105,407 episodes from the Norwegian Arthroplasty Register were used to model individual mortality risk over the first year after surgery using flexible parametric survival regression.Aims
Methods
Aims. To develop prediction models using machine-learning (ML) algorithms for 90-day and one-year mortality prediction in femoral neck fracture (FNF) patients aged 50 years or older based on the Hip fracture Evaluation with Alternatives of Total Hip arthroplasty versus Hemiarthroplasty (HEALTH) and Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trials. Methods. This study included 2,388 patients from the HEALTH and FAITH trials, with 90-day and one-year mortality proportions of 3.0% (71/2,388) and 6.4% (153/2,388), respectively. The mean age was 75.9 years (SD 10.8) and 65.9% of patients (1,574/2,388) were female. The algorithms included patient and injury characteristics. Six algorithms were developed, internally validated and evaluated across discrimination (c-statistic; discriminative ability between those with risk of mortality and those without),
Aims. This study aimed to compare the performance of survival prediction models for bone metastases of the extremities (BM-E) with pathological fractures in an Asian cohort, and investigate patient characteristics associated with survival. Methods. This retrospective cohort study included 469 patients, who underwent surgery for BM-E between January 2009 and March 2022 at a tertiary hospital in South Korea. Postoperative survival was calculated using the PATHFx3.0, SPRING13, OPTIModel, SORG, and IOR models. Model performance was assessed with area under the curve (AUC),
Aims. The Uppföljningsprogram för cerebral pares (CPUP) Hip Score distinguishes between children with cerebral palsy (CP) at different levels of risk for displacement of the hip. The score was constructed using data from Swedish children with CP, but has not been confirmed in any other population. The aim of this study was to determine the
Aims. Heterotopic ossification (HO) is a common complication after elbow trauma and can cause severe upper limb disability. Although multiple prognostic factors have been reported to be associated with the development of post-traumatic HO, no model has yet been able to combine these predictors more succinctly to convey prognostic information and medical measures to patients. Therefore, this study aimed to identify prognostic factors leading to the formation of HO after surgery for elbow trauma, and to establish and validate a nomogram to predict the probability of HO formation in such particular injuries. Methods. This multicentre case-control study comprised 200 patients with post-traumatic elbow HO and 229 patients who had elbow trauma but without HO formation between July 2019 and December 2020. Features possibly associated with HO formation were obtained. The least absolute shrinkage and selection operator regression model was used to optimize feature selection. Multivariable logistic regression analysis was applied to build the new nomogram: the Shanghai post-Traumatic Elbow Heterotopic Ossification Prediction model (STEHOP). STEHOP was validated by concordance index (C-index) and
Aims. The aim of this study was to develop and internally validate a prognostic nomogram to predict the probability of gaining a functional range of motion (ROM ≥ 120°) after open arthrolysis of the elbow in patients with post-traumatic stiffness of the elbow. Methods. We developed the Shanghai Prediction Model for Elbow Stiffness Surgical Outcome (SPESSO) based on a dataset of 551 patients who underwent open arthrolysis of the elbow in four institutions. Demographic and clinical characteristics were collected from medical records. The least absolute shrinkage and selection operator regression model was used to optimize the selection of relevant features. Multivariable logistic regression analysis was used to build the SPESSO. Its prediction performance was evaluated using the concordance index (C-index) and a
Aims. To develop and externally validate a parsimonious statistical prediction model of 90-day mortality after elective total hip arthroplasty (THA), and to provide a web calculator for clinical usage. Methods. We included 53,099 patients with cemented THA due to osteoarthritis from the Swedish Hip Arthroplasty Registry for model derivation and internal validation, as well as 125,428 patients from England and Wales recorded in the National Joint Register for England, Wales, Northern Ireland, the Isle of Man, and the States of Guernsey (NJR) for external model validation. A model was developed using a bootstrap ranking procedure with a least absolute shrinkage and selection operator (LASSO) logistic regression model combined with piecewise linear regression. Discriminative ability was evaluated by the area under the receiver operating characteristic curve (AUC).
Aims. To identify variables independently associated with same-day discharge (SDD) of patients following revision total knee arthroplasty (rTKA) and to develop machine learning algorithms to predict suitable candidates for outpatient rTKA. Methods. Data were obtained from the American College of Surgeons National Quality Improvement Programme (ACS-NSQIP) database from the years 2018 to 2020. Patients with elective, unilateral rTKA procedures and a total hospital length of stay between zero and four days were included. Demographic, preoperative, and intraoperative variables were analyzed. A multivariable logistic regression (MLR) model and various machine learning techniques were compared using area under the curve (AUC),
Aims. This study aimed to develop and validate a fully automated system that quantifies proximal femoral bone mineral density (BMD) from CT images. Methods. The study analyzed 978 pairs of hip CT and dual-energy X-ray absorptiometry (DXA) measurements of the proximal femur (DXA-BMD) collected from three institutions. From the CT images, the femur and a
Aims. The aim of this study was to identify factors associated with five-year cancer-related mortality in patients with limb and trunk soft-tissue sarcoma (STS) and develop and validate machine learning algorithms in order to predict five-year cancer-related mortality in these patients. Methods. Demographic, clinicopathological, and treatment variables of limb and trunk STS patients in the Surveillance, Epidemiology, and End Results Program (SEER) database from 2004 to 2017 were analyzed. Multivariable logistic regression was used to determine factors significantly associated with five-year cancer-related mortality. Various machine learning models were developed and compared using area under the curve (AUC),
Aims. Traditionally, total hip arthroplasty (THA) templating has been performed on anteroposterior (AP) pelvis radiographs. Recently, additional AP hip radiographs have been recommended for accurate measurement of the femoral offset (FO). To verify this claim, this study aimed to establish quantitative data of the measurement error of the FO in relation to leg position and X-ray source position using a newly developed geometric model and clinical data. Methods. We analyzed the FOs measured on AP hip and pelvis radiographs in a prospective consecutive series of 55 patients undergoing unilateral primary THA for hip osteoarthritis. To determine sample size, a power analysis was performed. Patients’ position and X-ray beam setting followed a standardized protocol to achieve reproducible projections. All images were calibrated with the KingMark
Aims. We aimed to develop a gene signature that predicts the occurrence of postmenopausal osteoporosis (PMOP) by studying its genetic mechanism. Methods. Five datasets were obtained from the Gene Expression Omnibus database. Unsupervised consensus cluster analysis was used to determine new PMOP subtypes. To determine the central genes and the core modules related to PMOP, the weighted gene co-expression network analysis (WCGNA) was applied. Gene Ontology enrichment analysis was used to explore the biological processes underlying key genes. Logistic regression univariate analysis was used to screen for statistically significant variables. Two algorithms were used to select important PMOP-related genes. A logistic regression model was used to construct the PMOP-related gene profile. The receiver operating characteristic area under the curve, Harrell’s concordance index, a
Aims. Our aim was to develop and validate nomograms that would predict the cumulative incidence of sarcoma-specific death (CISSD) and disease progression (CIDP) in patients with localized high-grade primary central and dedifferentiated chondrosarcoma. Methods. The study population consisted of 391 patients from two international sarcoma centres (development cohort) who had undergone definitive surgery for a localized high-grade (histological grade II or III) conventional primary central chondrosarcoma or dedifferentiated chondrosarcoma. Disease progression captured the first event of either metastasis or local recurrence. An independent cohort of 221 patients from three additional hospitals was used for external validation. Two nomograms were internally and externally validated for discrimination (c-index) and
Aims. To develop and internally validate a preoperative clinical prediction model for acute adjacent vertebral fracture (AVF) after vertebral augmentation to support preoperative decision-making, named the after vertebral augmentation (AVA) score. Methods. In this prognostic study, a multicentre, retrospective single-level vertebral augmentation cohort of 377 patients from six Japanese hospitals was used to derive an AVF prediction model. Backward stepwise selection (p < 0.05) was used to select preoperative clinical and imaging predictors for acute AVF after vertebral augmentation for up to one month, from 14 predictors. We assigned a score to each selected variable based on the regression coefficient and developed the AVA scoring system. We evaluated sensitivity and specificity for each cut-off, area under the curve (AUC), and
Aims. The incidence of bone metastases is between 20% to 75% depending on the type of cancer. As treatment improves, the number of patients who need surgical intervention is increasing. Identifying patients with a shorter life expectancy would allow surgical intervention with more durable reconstructions to be targeted to those most likely to benefit. While previous scoring systems have focused on surgical and oncological factors, there is a need to consider comorbidities and the physiological state of the patient, as these will also affect outcome. The primary aim of this study was to create a scoring system to estimate survival time in patients with bony metastases and to determine which factors may adversely affect this. Methods. This was a retrospective study which included all patients who had presented for surgery with metastatic bone disease. The data collected included patient, surgical, and oncological variables. Univariable and multivariable analysis identified which factors were associated with a survival time of less than six months and less than one year. A model to predict survival based on these factors was developed using Cox regression. Results. A total of 164 patients were included with a median survival time of 1.6 years (interquartile range 0.5 to 3.1) after surgery. On multivariable analysis, a higher American Society of Anesthesiologists grade (p < 0.001), a high white cell count (p = 0.002), hyponatraemia (p = 0.001), a preoperative resting heart rate of > 100 bpm (p = 0.052), and the type of primary cancer (p = 0.026) remained significant predictors of reduced survival time. The predictive model developed showed good discrimination and
Aims. The aim of this study was to explore the prognostic factors for postoperative neurological recovery and survival in patients with complete paralysis due to neoplastic epidural spinal cord compression. Patients and Methods. The medical records of 135 patients with complete paralysis due to neoplastic cord compression were retrospectively reviewed. Potential factors including the timing of surgery, muscular tone, and tumour characteristics were analyzed in relation to neurological recovery using logistical regression analysis. The association between neurological recovery and survival was analyzed using a Cox model. A nomogram was formulated to predict recovery. Results. A total of 52 patients (38.5%) achieved American Spinal Injury Association Impairment Scale (AIS) D or E recovery postoperatively. The timing of surgery (p = 0.003) was found to be significant in univariate analysis. In multivariate analysis, surgery within one week was associated with better neurological recovery than surgery within three weeks (p = 0.002), with a trend towards being associated with a better neurological recovery than surgery within one to two weeks (p = 0.597) and two to three weeks (p = 0.055). Age (p = 0.039) and muscle tone (p = 0.018) were also significant predictors. In Cox regression analysis, good neurological recovery (p = 0.004), benign tumours (p = 0.039), and primary tumours (p = 0.005) were associated with longer survival.
Objectives. The National Hip Fracture Database (NHFD) publishes hospital-level risk-adjusted mortality rates following hip fracture surgery in England, Wales and Northern Ireland. The performance of the risk model used by the NHFD was compared with the widely-used Nottingham Hip Fracture Score. Methods. Data from 94 hospitals on patients aged 60 to 110 who had hip fracture surgery between May 2013 and July 2013 were analysed. Data were linked to the Office for National Statistics (ONS) death register to calculate the 30-day mortality rate. Risk of death was predicted for each patient using the NHFD and Nottingham models in a development dataset using logistic regression to define the models’ coefficients. This was followed by testing the performance of these refined models in a second validation dataset. Results. The 30-day mortality rate was 5.36% in the validation dataset (n = 3861), slightly lower than the 6.40% in the development dataset (n = 4044). The NHFD and Nottingham models showed a slightly lower discrimination in the validation dataset compared with the development dataset, but both still displayed moderate discriminative power (c-statistic for NHFD = 0.71, 95% confidence interval (CI) 0.67 to 0.74; Nottingham model = 0.70, 95% CI 0.68 to 0.75). Both models defined similar ranges of predicted mortality risk (1% to 18%) in assessment of
Early and accurate prediction of hospital length-of-stay
(LOS) in patients undergoing knee replacement is important for economic
and operational reasons. Few studies have systematically developed
a multivariable model to predict LOS. We performed a retrospective
cohort study of 1609 patients aged ≥ 50 years who underwent elective,
primary total or unicompartmental knee replacements. Pre-operative
candidate predictors included patient demographics, knee function,
self-reported measures, surgical factors and discharge plans. In
order to develop the model, multivariable regression with bootstrap
internal validation was used. The median LOS for the sample was
four days (interquartile range 4 to 5). Statistically significant
predictors of longer stay included older age, greater number of comorbidities,
less knee flexion range of movement, frequent feelings of being
down and depressed, greater walking aid support required, total
(versus unicompartmental) knee replacement, bilateral
surgery, low-volume surgeon, absence of carer at home, and expectation
to receive step-down care. For ease of use, these ten variables were
used to construct a nomogram-based prediction model which showed
adequate predictive accuracy (optimism-corrected R. 2. =
0.32) and
To examine whether natural language processing (NLP) using a clinically based large language model (LLM) could be used to predict patient selection for total hip or total knee arthroplasty (THA/TKA) from routinely available free-text radiology reports. Data pre-processing and analyses were conducted according to the Artificial intelligence to Revolutionize the patient Care pathway in Hip and knEe aRthroplastY (ARCHERY) project protocol. This included use of de-identified Scottish regional clinical data of patients referred for consideration of THA/TKA, held in a secure data environment designed for artificial intelligence (AI) inference. Only preoperative radiology reports were included. NLP algorithms were based on the freely available GatorTron model, a LLM trained on over 82 billion words of de-identified clinical text. Two inference tasks were performed: assessment after model-fine tuning (50 Epochs and three cycles of k-fold cross validation), and external validation.Aims
Methods
Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of this study are to 1) provide an overview of current ML prediction models in orthopaedic trauma; 2) evaluate the completeness of reporting following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement; and 3) assess the risk of bias following the Prediction model Risk Of Bias Assessment Tool (PROBAST) tool. A systematic search screening 3,252 studies identified 45 ML-based prediction models in orthopaedic trauma up to January 2023. The TRIPOD statement assessed transparent reporting and the PROBAST tool the risk of bias.Aims
Methods
A substantial fraction of patients undergoing knee arthroplasty (KA) or hip arthroplasty (HA) do not achieve an improvement as high as the minimal clinically important difference (MCID), i.e. do not achieve a meaningful improvement. Using three patient-reported outcome measures (PROMs), our aim was: 1) to assess machine learning (ML), the simple pre-surgery PROM score, and logistic-regression (LR)-derived performance in their prediction of whether patients undergoing HA or KA achieve an improvement as high or higher than a calculated MCID; and 2) to test whether ML is able to outperform LR or pre-surgery PROM scores in predictive performance. MCIDs were derived using the change difference method in a sample of 1,843 HA and 1,546 KA patients. An artificial neural network, a gradient boosting machine, least absolute shrinkage and selection operator (LASSO) regression, ridge regression, elastic net, random forest, LR, and pre-surgery PROM scores were applied to predict MCID for the following PROMs: EuroQol five-dimension, five-level questionnaire (EQ-5D-5L), EQ visual analogue scale (EQ-VAS), Hip disability and Osteoarthritis Outcome Score-Physical Function Short-form (HOOS-PS), and Knee injury and Osteoarthritis Outcome Score-Physical Function Short-form (KOOS-PS).Aims
Methods
Micromotion of the polyethylene (PE) inlay may contribute to backside PE wear in addition to articulate wear of total knee arthroplasty (TKA). Using radiostereometric analysis (RSA) with tantalum beads in the PE inlay, we evaluated PE micromotion and its relationship to PE wear. A total of 23 patients with a mean age of 83 years (77 to 91), were available from a RSA study on cemented TKA with Maxim tibial components (Zimmer Biomet). PE inlay migration, PE wear, tibial component migration, and the anatomical knee axis were evaluated on weightbearing stereoradiographs. PE inlay wear was measured as the deepest penetration of the femoral component into the PE inlay.Aims
Methods
Prediction tools are instruments which are commonly used to estimate the prognosis in oncology and facilitate clinical decision-making in a more personalized manner. Their popularity is shown by the increasing numbers of prediction tools, which have been described in the medical literature. Many of these tools have been shown to be useful in the field of soft-tissue sarcoma of the extremities (eSTS). In this annotation, we aim to provide an overview of the available prediction tools for eSTS, provide an approach for clinicians to evaluate the performance and usefulness of the available tools for their own patients, and discuss their possible applications in the management of patients with an eSTS. Cite this article:
The February 2023 Trauma Roundup360 looks at: Masquelet versus bone transport in infected nonunion of tibia; Hyperbaric Oxygen for Lower Limb Trauma (HOLLT): an international multicentre randomized clinical trial; Is the T-shaped acetabular fracture really a “T”?; What causes cut-out of proximal femur nail anti-rotation device in intertrochanteric fractures?; Is the common femoral artery at risk with percutaneous fragility pelvis fixation?; Anterior pelvic ring pattern predicts displacement in lateral compression fractures; Differences in age-related characteristics among elderly patients with hip fractures.
The Oxford Shoulder Score (OSS) is a 12-item measure commonly used for the assessment of shoulder surgeries. This study explores whether computerized adaptive testing (CAT) provides a shortened, individually tailored questionnaire while maintaining test accuracy. A total of 16,238 preoperative OSS were available in the National Joint Registry (NJR) for England, Wales, Northern Ireland, the Isle of Man, and the States of Guernsey dataset (April 2012 to April 2022). Prior to CAT, the foundational item response theory (IRT) assumptions of unidimensionality, monotonicity, and local independence were established. CAT compared sequential item selection with stopping criteria set at standard error (SE) < 0.32 and SE < 0.45 (equivalent to reliability coefficients of 0.90 and 0.80) to full-length patient-reported outcome measure (PROM) precision.Aims
Methods
This study was designed to develop a model for predicting bone mineral density (BMD) loss of the femur after total hip arthroplasty (THA) using artificial intelligence (AI), and to identify factors that influence the prediction. Additionally, we virtually examined the efficacy of administration of bisphosphonate for cases with severe BMD loss based on the predictive model. The study included 538 joints that underwent primary THA. The patients were divided into groups using unsupervised time series clustering for five-year BMD loss of Gruen zone 7 postoperatively, and a machine-learning model to predict the BMD loss was developed. Additionally, the predictor for BMD loss was extracted using SHapley Additive exPlanations (SHAP). The patient-specific efficacy of bisphosphonate, which is the most important categorical predictor for BMD loss, was examined by calculating the change in predictive probability when hypothetically switching between the inclusion and exclusion of bisphosphonate.Aims
Methods
The June 2024 Hip & Pelvis Roundup360 looks at: Machine learning did not outperform conventional competing risk modelling to predict revision arthroplasty; Unravelling the risks: incidence and reoperation rates for femoral fractures post-total hip arthroplasty; Spinal versus general anaesthesia for hip arthroscopy: a COVID-19 pandemic- and opioid epidemic-driven study; Development and validation of a deep-learning model to predict total hip arthroplasty on radiographs; Ambulatory centres lead in same-day hip and knee arthroplasty success; Exploring the impact of smokeless tobacco on total hip arthroplasty outcomes: a deeper dive into postoperative complications.
The aim of this study was to investigate the agreement in interpretation of the quality of the paediatric hip ultrasound examination, the reliability of geometric and morphological assessment, and the relationship between these measurements. Four investigators evaluated 60 hip ultrasounds and assessed their quality based the standard plane of Graf et al. They measured geometric parameters, described the morphology of the hip, and assigned the Graf grade of dysplasia. They analyzed one self-selected image and one randomly selected image from the ultrasound series, and repeated the process four weeks later. The intra- and interobserver agreement, and correlations between various parameters were analyzed.Aims
Methods
The aim of this study was to evaluate the kinematics of the elbow following increasing length of the radius with implantation of radial head arthroplasties (RHAs) using dynamic radiostereometry (dRSA). Eight human donor arms were examined by dRSA during motor-controlled flexion and extension of the elbow with the forearm in an unloaded neutral position, and in pronation and supination with and without a 10 N valgus or varus load, respectively. The elbows were examined before and after RHA with stem lengths of anatomical size, + 2 mm, and + 4 mm. The ligaments were maintained intact by using a step-cut lateral humeral epicondylar osteotomy, allowing the RHAs to be repeatedly exchanged. Bone models were obtained from CT scans, and specialized software was used to match these models with the dRSA recordings. The flexion kinematics of the elbow were described using anatomical coordinate systems to define translations and rotations with six degrees of freedom.Aims
Methods
Polyethylene particulate wear debris continues to be implicated in the aetiology of aseptic loosening following knee arthroplasty. The Oxford unicompartmental knee arthroplasty employs a spherical femoral component and a fully congruous meniscal bearing to increase contact area and theoretically reduce the potential for polyethylene wear. This study measures the in vivo ten-year linear wear of the device, using a roentgenstereophotogrammetric technique. In this in vivo study, seven medial Oxford unicompartmental prostheses, which had been implanted ten years previously were studied. Stereo pairs of radiographs were acquired for each patient and the films were analysed using a roentgen stereophotogrammetric analysis
A novel enhanced cement fixation (EF) tibial implant with deeper cement pockets and a more roughened bonding surface was released to market for an existing total knee arthroplasty (TKA) system.This randomized controlled trial assessed fixation of the both the EF (ATTUNE S+) and standard (Std; ATTUNE S) using radiostereometric analysis. Overall, 50 subjects were randomized (21 EF-TKA and 23 Std-TKA in the final analysis), and had follow-up visits at six weeks, and six, 12, and 24 months to assess migration of the tibial component. Low viscosity bone cement with tobramycin was used in a standardized fashion for all subjects. Patient-reported outcome measure data was captured at preoperative and all postoperative visits.Aims
Methods
This study aimed to quantify the shoulder kinematics during an apprehension-relocation test in patients with anterior shoulder instability (ASI) and glenoid bone loss using the radiostereometric analysis (RSA) method. Kinematics were compared with the patient’s contralateral healthy shoulder. A total of 20 patients with ASI and > 10% glenoid bone loss and a healthy contralateral shoulder were included. RSA imaging of the patient’s shoulders was performed during a repeated apprehension-relocation test. Bone volume models were generated from CT scans, marked with anatomical coordinate systems, and aligned with the digitally reconstructed bone projections on the RSA images. The glenohumeral joint (GHJ) kinematics were evaluated in the anteroposterior and superoinferior direction of: the humeral head centre location relative to the glenoid centre; and the humeral head contact point location on the glenoid.Aims
Methods
Despite limited clinical scientific backing, an additional trochanteric stabilizing plate (TSP) has been advocated when treating unstable trochanteric fractures with a sliding hip screw (SHS). We aimed to explore whether the TSP would result in less post operative fracture motion, compared to SHS alone. Overall, 31 patients with AO/OTA 31-A2 trochanteric fractures were randomized to either a SHS alone or a SHS with an additional TSP. To compare postoperative fracture motion, radiostereometric analysis (RSA) was performed before and after weightbearing, and then at four, eight, 12, 26, and 52 weeks. With the “after weightbearing” images as baseline, we calculated translations and rotations, including shortening and medialization of the femoral shaft.Aims
Methods
In this study, we aimed to visualize the spatial distribution characteristics of femoral head necrosis using a novel measurement method. We retrospectively collected CT imaging data of 108 hips with non-traumatic osteonecrosis of the femoral head from 76 consecutive patients (mean age 34.3 years (SD 8.1), 56.58% male (n = 43)) in two clinical centres. The femoral head was divided into 288 standard units (based on the orientation of units within the femoral head, designated as N[Superior], S[Inferior], E[Anterior], and W[Posterior]) using a new measurement system called the longitude and latitude division system (LLDS). A computer-aided design (CAD) measurement tool was also developed to visualize the measurement of the spatial location of necrotic lesions in CT images. Two orthopaedic surgeons independently performed measurements, and the results were used to draw 2D and 3D heat maps of spatial distribution of necrotic lesions in the femoral head, and for statistical analysis.Aims
Methods
To map the Oxford Knee Score (OKS) and High Activity Arthroplasty Score (HAAS) items to a common scale, and to investigate the psychometric properties of this new scale for the measurement of knee health. Patient-reported outcome measure (PROM) data measuring knee health were obtained from the NHS PROMs dataset and Total or Partial Knee Arthroplasty Trial (TOPKAT). Assumptions for common scale modelling were tested. A graded response model (fitted to OKS item responses in the NHS PROMs dataset) was used as an anchor to calibrate paired HAAS items from the TOPKAT dataset. Information curves for the combined OKS-HAAS model were plotted. Bland-Altman analysis was used to compare common scale scores derived from OKS and HAAS items. A conversion table was developed to map between HAAS, OKS, and the common scale.Aims
Methods
Despite the vast quantities of published artificial intelligence (AI) algorithms that target trauma and orthopaedic applications, very few progress to inform clinical practice. One key reason for this is the lack of a clear pathway from development to deployment. In order to assist with this process, we have developed the Clinical Practice Integration of Artificial Intelligence (CPI-AI) framework – a five-stage approach to the clinical practice adoption of AI in the setting of trauma and orthopaedics, based on the IDEAL principles ( Cite this article:
Cemented hemiarthroplasty is an effective form of treatment for most patients with an intracapsular fracture of the hip. However, it remains unclear whether there are subgroups of patients who may benefit from the alternative operation of a modern uncemented hemiarthroplasty – the aim of this study was to investigate this issue. Knowledge about the heterogeneity of treatment effects is important for surgeons in order to target operations towards specific subgroups who would benefit the most. We used causal forest analysis to compare subgroup- and individual-level treatment effects between cemented and modern uncemented hemiarthroplasty in patients aged > 60 years with an intracapsular fracture of the hip, using data from the World Hip Trauma Evaluation 5 (WHiTE 5) multicentre randomized clinical trial. EuroQol five-dimension index scores were used to measure health-related quality of life at one, four, and 12 months postoperatively.Aims
Methods
The October 2023 Hip & Pelvis Roundup360 looks at: Femoroacetabular impingement syndrome at ten years – how do athletes do?; Venous thromboembolism in patients following total joint replacement: are transfusions to blame?; What changes in pelvic sagittal tilt occur 20 years after total hip arthroplasty?; Can stratified care in hip arthroscopy predict successful and unsuccessful outcomes?; Hip replacement into your nineties; Can large language models help with follow-up?; The most taxing of revisions – proximal femoral replacement for periprosthetic joint infection – what’s the benefit of dual mobility?
Dual-mobility acetabular components (DMCs) have improved total hip arthroplasty (THA) stability in femoral neck fractures (FNFs). In osteoarthritis, the direct anterior approach (DAA) has been promoted for improving early functional results compared with the posterolateral approach (PLA). The aim of this study was to compare these two approaches in FNF using DMC-THA. A prospective continuous cohort study was conducted on patients undergoing operation for FNF using DMC by DAA or PLA. Functional outcome was evaluated using the Harris Hip Score (HHS) and Parker score at three months and one year. Perioperative complications were recorded, and radiological component positioning evaluated.Aims
Methods
The aim of this study was to compare the migration of the femoral component, five years postoperatively, between patients with a highly cross-linked polyethylene (HXLPE) insert and those with a conventional polyethylene (PE) insert in an uncemented Triathlon fixed insert cruciate-retaining total knee arthroplasty (TKA). Secondary aims included clinical outcomes and patient-reported outcome measures (PROMs). We have previously reported the migration and outcome of the tibial components in these patients. A double-blinded randomized controlled trial was conducted including 96 TKAs. The migration of the femoral component was measured with radiostereometry (RSA) at three and six months and one, two, and five years postoperatively. PROMs were collected preoperatively and at all periods of follow-up.Aims
Methods
Robotic-assisted total knee arthroplasty (TKA) has proven higher accuracy, fewer alignment outliers, and improved short-term clinical outcomes when compared to conventional TKA. However, evidence of cost-effectiveness and individual superiority of one system over another is the subject of further research. Despite its growing adoption rate, published results are still limited and comparative studies are scarce. This review compares characteristics and performance of five currently available systems, focusing on the information and feedback each system provides to the surgeon, what the systems allow the surgeon to modify during the operation, and how each system then aids execution of the surgical plan. Cite this article: Abstract
Instability is a common cause of failure after total hip arthroplasty. A novel reverse total hip has been developed, with a femoral cup and acetabular ball, creating enhanced mechanical stability. The purpose of this study was to assess the implant fixation using radiostereometric analysis (RSA), and the clinical safety and efficacy of this novel design. Patients with end-stage osteoarthritis were enrolled in a prospective cohort at a single centre. The cohort consisted of 11 females and 11 males with mean age of 70.6 years (SD 3.5) and BMI of 31.0 kg/m2 (SD 5.7). Implant fixation was evaluated using RSA as well as Western Ontario and McMaster Universities Osteoarthritis Index, Harris Hip Score, Oxford Hip Score, Hip disability and Osteoarthritis Outcome Score, 38-item Short Form survey, and EuroQol five-dimension health questionnaire scores at two-year follow-up. At least one acetabular screw was used in all cases. RSA markers were inserted into the innominate bone and proximal femur with imaging at six weeks (baseline) and six, 12, and 24 months. Independent-samples Aims
Methods
Conventional patient-reported surveys, used for patients undergoing total hip arthroplasty (THA), are limited by subjectivity and recall bias. Objective functional evaluation, such as gait analysis, to delineate a patient’s functional capacity and customize surgical interventions, may address these shortcomings. This systematic review endeavours to investigate the application of objective functional assessments in appraising individuals undergoing THA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied. Eligible studies of THA patients that conducted at least one type of objective functional assessment both pre- and postoperatively were identified through Embase, Medline/PubMed, and Cochrane Central database-searching from inception to 15 September 2023. The assessments included were subgrouped for analysis: gait analysis, motion analysis, wearables, and strength tests.Aims
Methods
The August 2023 Knee Roundup360 looks at: Curettage and cementation of giant cell tumour of bone: is arthritis a given?; Anterior knee pain following total knee arthroplasty: does the patellar cement-bone interface affect postoperative anterior knee pain?; Nickel allergy and total knee arthroplasty; The use of artificial intelligence for the prediction of periprosthetic joint infection following aseptic revision total knee arthroplasty; Ambulatory unicompartmental knee arthroplasty: development of a patient selection tool using machine learning; Femoral asymmetry: a missing piece in knee alignment; Needle arthroscopy – a benefit to patients in the outpatient setting; Can lateral unicompartmental knees be done in a day-case setting?
Arthroplasty surgery of the knee and hip is performed in two to three million patients annually. Periprosthetic joint infections occur in 4% of these patients. Debridement, antibiotics, and implant retention (DAIR) surgery aimed at cleaning the infected prosthesis often fails, subsequently requiring invasive revision of the complete prosthetic reconstruction. Infection-specific imaging may help to guide DAIR. In this study, we evaluated a bacteria-specific hybrid tracer (99mTc-UBI29-41-Cy5) and its ability to visualize the bacterial load on femoral implants using clinical-grade image guidance methods.
99mTc-UBI29-41-Cy5 specificity for Aims
Methods
The primary aim of this trial was to compare the subsidence of two similar hydroxyapatite-coated titanium femoral components from different manufacturers. Secondary aims were to compare rotational migration (anteversion/retroversion and varus/valgus tilt) and patient-reported outcome measures between both femoral components. Patients were randomized to receive one of the two femoral components (Avenir or Corail) during their primary total hip arthroplasty between August 2018 and September 2020. Radiostereometric analysis examinations at six, 12, and 24 months were used to assess the migration of each implanted femoral component compared to a baseline assessment. Patient-reported outcome measures were also recorded for these same timepoints. Overall, 50 patients were enrolled (62% male (n = 31), with a mean age of 65.7 years (SD 7.3), and mean BMI of 30.2 kg/m2 (SD 5.2)).Aims
Methods
The aim of this study was to investigate the global and local impact of fat on bone in obesity by using the diet-induced obese (DIO) mouse model. In this study, we generated a diet-induced mouse model of obesity to conduct lipidomic and 3D imaging assessments of bone marrow fat, and evaluated the correlated bone adaptation indices and bone mechanical properties.Aims
Methods
The primary objective of this study was to compare the five-year tibial component migration and wear between highly crosslinked polyethylene (HXLPE) inserts and conventional polyethylene (PE) inserts of the uncemented Triathlon fixed insert cruciate-retaining total knee arthroplasty (TKA). Secondary objectives included clinical outcomes and patient-reported outcome measures (PROMs). A double-blinded, randomized study was conducted including 96 TKAs. Tibial component migration and insert wear were measured with radiostereometric analysis (RSA) at three, six, 12, 24, and 60 months postoperatively. PROMS were collected preoperatively and at all follow-up timepoints.Aims
Methods